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mvpa2.kernels.npΒΆ

Kernels for Gaussian Process Regression and Classification.

Inheritance diagram of mvpa2.kernels.np

Functions

squared_euclidean_distance(data1[, data2, ...]) Compute weighted euclidean distance matrix between two datasets.

Classes

ConditionalAttribute([enabled]) Simple container intended to conditionally store the value
ConstantKernel(*args, **kwargs) The constant kernel class.
ExponentialKernel(*args, **kwargs) The Exponential kernel class.
GeneralizedLinearKernel(*args, **kwargs) The linear kernel class.
LinearKernel(*args, **kwargs) Simple linear kernel: K(a,b) = a*b.T
Matern_3_2Kernel([length_scale, sigma_f, ...]) The Matern kernel class for the case ni=3/2 or ni=5/2.
Matern_5_2Kernel(**kwargs) The Matern kernel class for the case ni=5/2.
NumpyKernel(*args, **kwargs) A Kernel object with internal representation as a 2d numpy array
Parameter(default[, ro, index, value, name, doc]) This class shall serve as a representation of a parameter.
PolyKernel(*args, **kwargs) Polynomial kernel: K(a,b) = (gamma*a*b.T+coef0)**degree
RationalQuadraticKernel([length_scale, ...]) The Rational Quadratic (RQ) kernel class.
RbfKernel(*args, **kwargs) Radial basis function (aka Gausian, aka ) kernel
SquaredExponentialKernel([length_scale, sigma_f]) The Squared Exponential kernel class.

Exceptions

ConditionalAttribute([enabled]) Simple container intended to conditionally store the value
ConstantKernel(*args, **kwargs) The constant kernel class.
ExponentialKernel(*args, **kwargs) The Exponential kernel class.
GeneralizedLinearKernel(*args, **kwargs) The linear kernel class.
LinearKernel(*args, **kwargs) Simple linear kernel: K(a,b) = a*b.T
Matern_3_2Kernel([length_scale, sigma_f, ...]) The Matern kernel class for the case ni=3/2 or ni=5/2.
Matern_5_2Kernel(**kwargs) The Matern kernel class for the case ni=5/2.
NumpyKernel(*args, **kwargs) A Kernel object with internal representation as a 2d numpy array
Parameter(default[, ro, index, value, name, doc]) This class shall serve as a representation of a parameter.
PolyKernel(*args, **kwargs) Polynomial kernel: K(a,b) = (gamma*a*b.T+coef0)**degree
RationalQuadraticKernel([length_scale, ...]) The Rational Quadratic (RQ) kernel class.
RbfKernel(*args, **kwargs) Radial basis function (aka Gausian, aka ) kernel
SquaredExponentialKernel([length_scale, sigma_f]) The Squared Exponential kernel class.

NeuroDebian

NITRC-listed